543 search results - page 9 / 109 » Nonlinear principal component analysis of noisy data |
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
Independent component analysis (ICA) is not only popular for blind source separation but also for unsupervised learning when the observations can be decomposed into some independe...
ICIP
2001
IEEE
14 years 9 months ago
2001
IEEE
In this paper we address the problem of registering 3D scattered data by the mean of a statistical shape model. This model is built from a training set on which a principal compon...
IGARSS
2009
13 years 5 months ago
2009
Kernel Principal Component Analysis (KPCA) is investigated for feature extraction from hyperspectral remotesensing data. Features extracted using KPCA are used to construct the Ex...
ESANN
2007
13 years 9 months ago
2007
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
ECML
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...